AI Engineer Jobs at Whoop with Visa Sponsorship
Whoop builds performance technology at the intersection of health science and machine learning, and AI Engineers here work on real-time biosignal processing, predictive modeling, and personalized health insights. Whoop has an active sponsorship track record for technical roles and supports H-1B, OPT, and TN pathways.
See All AI Engineer at Whoop JobsOverview
Showing 5 of 25+ AI Engineer Jobs at Whoop jobs


Have you applied for this role?


Have you applied for this role?


Have you applied for this role?


Have you applied for this role?


Have you applied for this role?
See all 25+ AI Engineer Jobs at Whoop
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Engineer Jobs at Whoop.
Get Access To All Jobs
INTRODUCTION
At WHOOP, we’re on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level and live longer by using AI to transform continuous physiological data into clear insights and actionable recommendations. Our AI platform is central to this mission, turning raw physiological signals into trusted, personalized guidance that members can act on every day. WHOOP is hiring a Senior AI/ML Engineer to help scale the intelligence layer behind WHOOP’s AI-powered experiences, including WHOOP Coach, AI-powered Support, and new intelligent features across the product. In this role, you will own core components of the AI Platform that power our internal AI Studio: evaluation pipelines, fine-tuning workflows, LLM observability, and experimentation tooling. You will partner closely with product and data science to translate real member needs into reliable, impactful AI systems that improve continuously based on real-world usage.
Responsibilities
- Design, build, and operate production AI systems and scaffolding around language models that power conversational, predictive, and generative capabilities across WHOOP products.
- Lead end-to-end AI system initiatives spanning problem definition, data flows, dataset design, evaluation harnesses, deployment, and iteration in close partnership with data science and product.
- Build and maintain pipelines for collecting, curating, and reshaping messy, multi-source data into high-quality, well-structured training and evaluation datasets for language model–based systems.
- Operationalize fine-tuning and evaluation workflows for large language models behind member-facing features such as WHOOP Coach and AI Support, including defining datasets, labels, and taxonomies that reflect real member needs.
- Develop tooling and frameworks that make experimentation, offline/online evaluation, and model deployment faster, safer, and more repeatable, including robust observability for AI features in production.
- Build and maintain feedback loops that connect real member interactions, offline evaluations, and training data updates so that models improve continuously based on real-world behavior.
- Mentor other engineers and data scientists, share best practices in applied AI/ML, and help elevate the overall technical bar of the AI Platform team.
QUALIFICATIONS
- 3+ years of experience in applied machine learning, AI engineering, or ML-focused software engineering roles, including significant work in production environments.
- Hands-on experience building with modern language models (open-weight or API-based), including prompt design, fine-tuning, and rigorous evaluation.
- Solid working understanding of ML fundamentals (dataset construction, feature engineering, training workflows, evaluation metrics, experiment design) sufficient to make good engineering tradeoffs and partner effectively with data scientists.
- Familiarity with modern LLM training and alignment techniques such as supervised fine-tuning (SFT), direct preference optimization (DPO), and reinforcement learning (RL), and how they influence data requirements, evaluation strategies, and system design in production.
- Proven track record building, shipping, and operating ML-powered systems end to end, from data pipelines (batch and/or streaming) that transform large datasets into usable training and evaluation sets to production deployments with inference optimization, observability, and lifecycle management.
- Strong proficiency in data manipulation and analysis, including working with messy, multi-source, and semi-structured data and translating product questions into well-defined datasets, labels, and evaluation splits.
- Familiarity with best practices for secure, privacy-aware AI and working with sensitive data.
- Excellent communication and collaboration skills, with the ability to influence across teams and drive alignment on technical direction.
LOCATION
This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.
Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
COMPENSATION
The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.
The U.S. base salary range for this full-time position is $150,000 - $210,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

INTRODUCTION
At WHOOP, we’re on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level and live longer by using AI to transform continuous physiological data into clear insights and actionable recommendations. Our AI platform is central to this mission, turning raw physiological signals into trusted, personalized guidance that members can act on every day. WHOOP is hiring a Senior AI/ML Engineer to help scale the intelligence layer behind WHOOP’s AI-powered experiences, including WHOOP Coach, AI-powered Support, and new intelligent features across the product. In this role, you will own core components of the AI Platform that power our internal AI Studio: evaluation pipelines, fine-tuning workflows, LLM observability, and experimentation tooling. You will partner closely with product and data science to translate real member needs into reliable, impactful AI systems that improve continuously based on real-world usage.
Responsibilities
- Design, build, and operate production AI systems and scaffolding around language models that power conversational, predictive, and generative capabilities across WHOOP products.
- Lead end-to-end AI system initiatives spanning problem definition, data flows, dataset design, evaluation harnesses, deployment, and iteration in close partnership with data science and product.
- Build and maintain pipelines for collecting, curating, and reshaping messy, multi-source data into high-quality, well-structured training and evaluation datasets for language model–based systems.
- Operationalize fine-tuning and evaluation workflows for large language models behind member-facing features such as WHOOP Coach and AI Support, including defining datasets, labels, and taxonomies that reflect real member needs.
- Develop tooling and frameworks that make experimentation, offline/online evaluation, and model deployment faster, safer, and more repeatable, including robust observability for AI features in production.
- Build and maintain feedback loops that connect real member interactions, offline evaluations, and training data updates so that models improve continuously based on real-world behavior.
- Mentor other engineers and data scientists, share best practices in applied AI/ML, and help elevate the overall technical bar of the AI Platform team.
QUALIFICATIONS
- 3+ years of experience in applied machine learning, AI engineering, or ML-focused software engineering roles, including significant work in production environments.
- Hands-on experience building with modern language models (open-weight or API-based), including prompt design, fine-tuning, and rigorous evaluation.
- Solid working understanding of ML fundamentals (dataset construction, feature engineering, training workflows, evaluation metrics, experiment design) sufficient to make good engineering tradeoffs and partner effectively with data scientists.
- Familiarity with modern LLM training and alignment techniques such as supervised fine-tuning (SFT), direct preference optimization (DPO), and reinforcement learning (RL), and how they influence data requirements, evaluation strategies, and system design in production.
- Proven track record building, shipping, and operating ML-powered systems end to end, from data pipelines (batch and/or streaming) that transform large datasets into usable training and evaluation sets to production deployments with inference optimization, observability, and lifecycle management.
- Strong proficiency in data manipulation and analysis, including working with messy, multi-source, and semi-structured data and translating product questions into well-defined datasets, labels, and evaluation splits.
- Familiarity with best practices for secure, privacy-aware AI and working with sensitive data.
- Excellent communication and collaboration skills, with the ability to influence across teams and drive alignment on technical direction.
LOCATION
This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.
Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
COMPENSATION
The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.
The U.S. base salary range for this full-time position is $150,000 - $210,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training. In addition to the base salary, the successful candidate will also receive benefits and a generous equity package. These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.
See all 25+ AI Engineer at Whoop jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Engineer at Whoop roles.
Get Access To All JobsTips for Finding AI Engineer Jobs at Whoop Jobs
Frame your ML work around biosignal data
Whoop's AI work centers on wearable sensor data, sleep staging, and physiological pattern recognition. Tailor your portfolio and resume to show experience with time-series models, signal processing, or health-adjacent datasets before you apply.
Confirm sponsorship willingness before interviewing
Not every AI Engineer opening at Whoop will explicitly list sponsorship in the job post. Email the recruiter directly after applying to confirm the role supports your visa type, so you don't invest weeks in a process that stalls at offer stage.
Time your OPT application to hiring cycles
Whoop tends to hire AI talent on a rolling basis, but STEM OPT extensions take up to 90 days to process through USCIS. File your STEM OPT extension before your initial OPT expires to stay continuously work-authorized through onboarding and beyond.
Use Migrate Mate to filter verified sponsoring roles
Search for AI Engineer roles at Whoop that are confirmed to support visa sponsorship using Migrate Mate. It filters out roles that won't sponsor, saving you from applying blind to positions that will stall at the offer stage.
Prepare for a specialty occupation showing early
For H-1B petitions, USCIS scrutinizes whether the role qualifies as a specialty occupation. Gather documentation now showing your AI Engineer position requires a bachelor's degree or higher in a specific technical field, such as computer science or applied mathematics.
AI Engineer at Whoop jobs are hiring across the US. Find yours.
Find AI Engineer at Whoop JobsFrequently Asked Questions
Does Whoop sponsor H-1B visas for AI Engineers?
Yes, Whoop has a documented track record of sponsoring H-1B visas for technical roles including AI Engineers. If you're in the H-1B cap lottery, your employer must file the registration in March for an October 1 start. Confirm sponsorship availability with the recruiter early in the process, as it can vary by team or budget cycle.
Which visa types are commonly used for AI Engineer roles at Whoop?
Whoop supports H-1B, F-1 OPT, F-1 CPT, and TN visas for AI Engineer positions. F-1 OPT and CPT are common entry points for recent graduates, with STEM OPT providing up to three years of work authorization. The TN visa is available to Canadian and Mexican nationals in qualifying technical occupations. H-1B remains the most common long-term pathway.
How do I apply for AI Engineer jobs at Whoop?
Browse open AI Engineer roles directly on Whoop's careers page or through Migrate Mate, which filters for positions with confirmed visa sponsorship. Tailor your application to highlight experience with machine learning on sensor or health data. Reach out to the recruiter after applying to confirm your visa type is supported before the process advances.
What qualifications are expected for AI Engineer roles at Whoop?
Whoop typically looks for candidates with a bachelor's or master's degree in computer science, electrical engineering, applied mathematics, or a related field. Hands-on experience with deep learning frameworks, time-series analysis, and production ML systems is expected. Experience with wearable or biomedical data is a meaningful differentiator given Whoop's core product focus.
How do I manage the timeline between a job offer and my visa start date at Whoop?
If you're transitioning from OPT to H-1B, you can use the cap-gap rule to stay authorized between your OPT expiration and the October 1 H-1B start date, provided your employer filed before the deadline. For TN holders, status can be renewed at the border or through USCIS without waiting for a new fiscal year.
See which AI Engineer at Whoop employers are hiring and sponsoring visas right now.
Search AI Engineer at Whoop Jobs